code: def normalize(clip, mean, std, inplace=False):
      if not _is_tensor_clip(clip):
          raise TypeError("tensor is not a torch clip.")
  
      if not inplace:
          clip = clip.clone()
  
      dtype = clip.dtype
      mean = torch.as_tensor(mean, dtype=dtype, device=clip.device)
      std = torch.as_tensor(std, dtype=dtype, device=clip.device)
      clip.sub_(mean[:, None, None, None]).div_(
          std[:, None, None, None]
      )
  
      return clip
  
file_path: gluon-cv/gluoncv/torch/data/transforms/videotransforms/functional.py
imports: import numbers
  import cv2
  import numpy
  import PIL
  import torch
label_desc: Use image node_id 5 for calling a global function with example usage: normalize(clip, mean, std, inplace) and returns: clip